Examples of security on information processing devices such as a personal computer (hereinafter referred to as a PC) include personal authentication based on biometric information (biometrics). When a fingerprint is used in biometric personal authentication, the fingerprint is collected from a finger of a user as image information using a capacitive fingerprint sensor or optical fingerprint sensor. The fingerprint of the user is collected as image information about a pattern made up of, for example, ridges which can touch a touch surface of the fingerprint sensor and valleys which does not touch the touch surface. Feature information is extracted from biometric data on a collected fingerprint image. Then, by matching the extracted feature information against pre-registered feature information, it is determined whether or not the user is really who he/she claims to be, i.e., personal authentication is performed. Examples of feature information on a fingerprint image as biometric data include positional information on ridge bifurcations or ridge endings of ridges. Incidentally, the biometric data is data, such as a fingerprint image, collected from a living body of the user. The feature information is information about features of the user's living body and is extracted from the biometric data.
Also, methods for matching entered biometric data or feature information against registered biometric data or feature information include a method known as 1:N matching. The 1:N matching is a method for identifying biometric data or feature information of a matching user out of multiple items of pre-registered biometric data or feature information when biometric data of a user is entered, and does not involve identifier input or other similar processes for identifying the user. The 1:N matching involves a complicated process when the entered biometric data or feature information is matched against all the registered biometric data or feature information. Therefore, matching is sometimes done after narrowing down the biometric data or feature information which can be match candidates. For example, there is a technique which, using classification into classes, narrows down match candidates to biometric data or feature information registered in classes into which entered biometric data or feature information is classified based on similarity of biometric data.